This specification generally relates to search engines.
While search engine results often get users ‘into the ballpark,’ it is increasingly common for users to have to reformulate their queries to locate a desired web resource. Today, this successive query reformulation process is manual, increasing the overall time required for a user to reach the desired search result
One way to attempt to reduce this amount of time is to work on improving initial result sets, using what might be called the ‘perfect search engine’ hypothesis. Under this hypothesis, with sufficient contextual information about the user, the perfect search engine should be able to perfectly derive the user's intent and to locate a desired web resource based on the user's input query.
Practically speaking, however, to succeed under this hypothesis, the user's original search query would have to be highly disambiguated by query content and/or by extensive knowledge of the user. The average user, however, is unlikely to enter such highly disambiguated original queries, and is also unlikely to be comfortable with the level of history collection necessary to clearly disambiguate results. In the future, the phrasing of original queries is likely to remain terse and simplistic, providing just enough information to obtain a broad result set that requires iterative reformulation for final success.